As decision-makers tackle the challenge of adapting Bay of Fundy dykelands to climate change, they need to understand who uses and values dykelands and salt marshes, and for what. This new paper in Ocean and Coastal Management, Comparing cultural ecosystem service delivery in dykelands and marshes using Instagram: A case of the Cornwallis (Jijuktu’kwejk) River, Nova Scotia, Canada, used four months of geocoded Instagram data to understand the cultural ecosystem service (CES) tradeoffs that might result from removing/realigning dykes and restoring salt marshes where dykelands can’t be sustained. Dykelands provide a much wider set of CES for a wider demographic than do marshes for this set of social media users. However, a big surprise is that while salt marshes were present in many photos they were not named as such; users spoke only about the dykes and dykelands behind those marshes. As such, the marsh CES in the dataset came from visitors to an impounded freshwater wetland trail which is a local attraction walkable from the downtown centre of Kentville. Many of the messages triangulate well with the 2016 online Q survey I ran with Nova Scotians about the same topic and the paper provides another nice case study as to the utility of social media data for social impact assessment. One of the really great things about this paper is that it is a real ‘lab’ output. The work was initiated as a follow-up to that 2016 study and to inform the new ResNet work when I knew Camille was going to be joining as an intern from AgroCampus Ouest. PhD student Yan collected a few months of Instagram posts for Camille to analyze with her help, postdoc Tuihedur helped with statistics, and then Yan picked it up again to write up after Camille went back to France. I’m proud of this paper and this collaborative team.
Yan Chen was in Toronto again for Social Media & Society, this time presenting collaborative work that was initiated by French intern Camille Caesemaecker, from Agrocampus Ouest. This has led Yan to thinking about a new kind of landscape change using Instagram, after her hydroelectricity work: understanding perceptions of the Bay of Fundy dykelands versus the wetlands they replaced. Those dykelands are becoming ever more difficult to sustain under sea level and storm conditions associated with climate change, and some will have to be realigned and/or restored to salt marsh. This work based on four months of Instagram support the strong female pro-dykeland factor–concerned about culture and recreation–also found through Q-method a few years ago. Nice when triangulation happens.
The second paper from Yan Chen’s MES thesis is now out in Society and Natural Resources, Leveraging social media to understand younger people’s perceptions and use of hydroelectric energy landscapes. It is a research note demonstrating the utility of manual coding and conceptual mapping of a year of Instagram images around two hydroelectricity sites to predict how changes might affect young residents. Unlike her first thesis paper in Landscape and Urban Planning, which carried out spatial mapping of value ‘hotspots’–a method widespread in today’s growing literature on cultural ecosystem services–this paper makes statistical links between features, activities and values conveyed through Instagram. The diagrams provide insight to the lifestyle and emotions associated with different landscape features, some changeable with hydro development or removal, and informs our new work on conservation culturomics for social impact assessment. Yan continues to drive this work as an IDPhD student. Congratulations, Yan.
Yan Chen is wrapping up a few days in Singapore for the NSF-funded Research Coordination Network (RCN) in Science, Engineering and Education for Sustainability (SEES) on Putting Sustainability into Convergence: Connecting Data, People, and Systems. This international workshop has been diverse in attendees and disciplines. Yan reflected, “The most discussed question is how people from different disciplines can collaborate. There are many scholars like me, as social scientists who are using sophisticated data analysis models; while others are engineers working on social issues. We both, at a certain degree, struggle in ‘cultural shocks’ between different disciplines.” It’s been a great opportunity for her to workshop with similarly cross-cutting folks. She described her session as discussing, “data sources, sizes, validity, sharing, proxies, and so on. …. [agreeing] that data or method cannot develop only on the technologies, but has to answer certain questions. For social scientists, finding a good mechanism of data sharing or archiving may be very useful. Also, how to cope with the rapidly developing technologies will be another challenge for us.” Thanks to SSHRC for supporting Yan’s trip, via Mike Smit’s Insight Grant, on which I’m a CI, Assessing the social impacts of hydroelectricity-driven landscape changing using text, images and archives: a Big Data approach.
I’m not on Facebook. Never have been. Or Twitter. Or Instagram. Certainly not SnapChat or any of those newfangled things. But as a social scientist I’ve increasingly found useful the data that other people make public in such settings. Some reasons are pragmatic. The public has become exhausted by surveys, and are too busy to participate in interviews and workshops, at the same time that environmentally minded graduate students have become increasingly less likely to have drivers’ licenses and thus less able to head out on field work to run them. Human ethics research boards are generally unconcerned with data that people voluntarily place in the public domain, allowing quick pilot work using social media across a range of topics and publics. If you take user agreements and settings literally and assume that those data have been volunteered, it is quite easy to be ethical by aggregation and citation, like you would any source. Finally, I believe there is very real understanding to be gained by using such data as proxies to understand human values, preferences, behaviours, and yearnings. My qualitative methods course finished up this week with presentations, and it took my breath away what insight the students gained over a month on topics as diverse as sexually transmitted disease infection, sustainable food conceptualizations, and human disturbance of migratory shorebirds thanks to posts on Reddit and Instagram.
So then comes the recent horrifying news over Facebook and its business model: unscrupulously selling access to large volumes of personal data to even less scrupulous companies like Cambridge Analytica. So what do I do now, besides a quick (and perhaps smug) wipe of the brow with relief that I did not aid in either Trump or Brexit? The furor suggests that many people, maybe even some of the same ones who so clearly cherish unknown followers, are not aware their data is available to people like me. They may not see my intentions differently than the infamous personality test that fed Cambridge Analytica, for instance if I advertise a scholarly survey via Facebook to target a very specific group not otherwise easy to capture. Moreover, how implicated might I feel if I paid them for that access, knowing now what kind of algorithms are driving that cleverness? Perhaps the lesson for researchers is the same as the lessons for social media users more generally; a somewhat Methodist moral that if something is effortless, there may be something wrong with it. Yet I will mourn the loss of access to social riches that will inevitably follow this news.